Cochrane Aaron, Rosedahl Luke, Tamaki Masako, Watanabe Takeo, Sasaki Yuka
Brown University, Rhode Island, United States.
RIKEN, Saitama, Japan.
bioRxiv. 2025 Jun 10:2025.03.31.646339. doi: 10.1101/2025.03.31.646339.
Neural excitation/inhibition (E/I) ratio is dynamically regulated on multiple timescales. Adaptive changes in E/I ratio can support healthy development, learning, and cognition, while disordered E/I ratio has been implicated in neurodevelopmental disorders, neurodegenerative disorders, and states of impaired vigilance. There has been growing interest in inferring E/I ratio from efficient and noninvasive measurements such as electroencephalography (EEG), and several algorithms have been proposed to estimate E/I ratio from EEG. Despite promising results, there has been a lack of validation studies testing the underlying neurochemical changes leading to increased or decreased EEG-based E/I ratio. Here, using concurrent EEG and magnetic resonance spectroscopy (MRS) for over an hour, we assessed which algorithm of EEG-based E/I ratio best matched with MRS-based E/I ratio in humans of both sexes. The MRS-based E/I ratio was obtained by the ratio of glutamate concentration to GABA concentration. We applied 10 candidate indices of EEG-based E/I ratio using four approaches in several spontaneous frequency bands. Uniquely, we quantified the associations between the EEG-based E/I ratio and MRS-based E/I ratio separately for between-subjects and within-subjects variations. We found that each EEG-based E/I algorithm showed reliable and positive associations with MRS-based E/I, and especially EEG-based E/I ratio in alpha band with a criticality theory based approach showed the best association to the MRS-based E/I ratio. While these associations were evident for between-subjects comparisons, they were quite weak for within-subjects comparisons. These results suggest that EEG-based E/I algorithms are likely to reflect, at least in part, relative concentrations of glutamate and GABA.
神经兴奋/抑制(E/I)比率在多个时间尺度上受到动态调节。E/I比率的适应性变化有助于健康发育、学习和认知,而E/I比率紊乱与神经发育障碍、神经退行性疾病以及警觉性受损状态有关。人们越来越有兴趣从脑电图(EEG)等高效且非侵入性的测量中推断E/I比率,并且已经提出了几种从EEG估计E/I比率的算法。尽管取得了有希望的结果,但缺乏验证研究来测试导致基于EEG的E/I比率升高或降低的潜在神经化学变化。在这里,我们使用同步EEG和磁共振波谱(MRS)超过一小时,评估了哪种基于EEG的E/I比率算法在男女受试者中与基于MRS的E/I比率最匹配。基于MRS的E/I比率通过谷氨酸浓度与GABA浓度的比率获得。我们在几个自发频段中使用四种方法应用了10个基于EEG的E/I比率候选指标。独特的是,我们分别针对受试者间和受试者内的变化量化了基于EEG的E/I比率与基于MRS的E/I比率之间的关联。我们发现,每种基于EEG的E/I算法都与基于MRS的E/I显示出可靠的正相关,特别是基于临界理论方法的α频段基于EEG的E/I比率与基于MRS的E/I比率显示出最佳关联。虽然这些关联在受试者间比较中很明显,但在受试者内比较中却相当弱。这些结果表明,基于EEG的E/I算法可能至少部分反映了谷氨酸和GABA的相对浓度。